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  <title>Classifier results - Classifier tests</title>
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<h1>Classifier tests</h1>
<p>
  Test Duration: 518.062s
</p>





  <table class="resultsTable" width="100%">
    <tr><th colspan="3" class="header passed">Passed Tests</th></tr>
              <tr>
        <td colspan="3" class="group">com.meum.classifier.test.MutationModifierTests</td>
      </tr>
      
<tr>
  <td class="method">
          testConstModifier
      </td>
  <td class="duration">
    6.703s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"gbpeur", ConstModifier, 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 gbpeur ConstModifier1<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: ConstModifier}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, ConstModifier]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg10&gt;1.125) ? (SELL) : ((arg6&gt;1.068) ? ((arg5&gt;1.101) ? ((arg0&gt;1.12) ? (SELL) : ((arg1&gt;1.12) ? (BUY) : ((arg14&gt;1.113) ? (SELL) : ((arg8&gt;1.087) ? (BUY) : ((arg4&gt;1.084) ? (SELL) : ((arg9&gt;1.128) ? (SELL) : (EVIL))))))) : (BUY)) : ((arg14&gt;1.113) ? (SELL) : ((arg11&gt;1.106) ? ((arg7&gt;1.102) ? (SELL) : (EVIL)) : (SELL))))<br />
                                Base fitness: 0.05555555555555555<br />
                                Test set base fitness: 0.6666666666666666<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testConstModifier
      </td>
  <td class="duration">
    6.390s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"chfeur", ConstModifier, 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 chfeur ConstModifier0<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: ConstModifier}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, ConstModifier]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg7&gt;0.664) ? (EVIL) : ((arg0&gt;0.662) ? ((arg14&gt;0.662) ? (SELL) : (BUY)) : ((arg10&gt;0.662) ? ((arg4&gt;0.66) ? (BUY) : (SELL)) : ((arg8&gt;0.662) ? ((arg3&gt;0.66) ? (BUY) : (SELL)) : ((arg4&gt;0.663) ? (BUY) : ((arg14&gt;0.661) ? (EVIL) : ((arg9&gt;0.668) ? (SELL) : ((arg11&gt;0.661) ? (EVIL) : ((arg3&gt;0.663) ? (SELL) : (BUY)))))))))<br />
                                Base fitness: 0.037037037037037035<br />
                                Test set base fitness: 0.4444444444444444<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testConstModifier
      </td>
  <td class="duration">
    6.532s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"cadeur", ConstModifier, 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 cadeur ConstModifier2<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: ConstModifier}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, ConstModifier]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg4&gt;0.628) ? ((arg2&gt;0.634) ? ((arg11&gt;0.636) ? ((arg9&gt;0.654) ? ((arg12&gt;0.663) ? ((arg1&gt;0.632) ? (BUY) : (EVIL)) : ((arg14&gt;0.634) ? ((arg6&gt;0.654) ? (SELL) : (BUY)) : (EVIL))) : (SELL)) : (BUY)) : ((arg1&gt;0.638) ? (SELL) : (BUY))) : ((arg5&gt;0.625) ? (SELL) : (BUY))<br />
                                Base fitness: 0.08333333333333333<br />
                                Test set base fitness: 1.0<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    6.375s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"chfeur", [50<=gen<100; +0, 100<=gen<150; +0, 150<=gen<200; +1, 200<=gen<250; +1, 250<=gen<300; +2, 350<=gen<400; +2, 400<=gen<450; +2], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 chfeur RangeModifier1<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +0, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +1, 200&lt;=gen&lt;250; +1, 250&lt;=gen&lt;300; +2, 350&lt;=gen&lt;400; +2, 400&lt;=gen&lt;450; +2]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +0, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +1, 200&lt;=gen&lt;250; +1, 250&lt;=gen&lt;300; +2, 350&lt;=gen&lt;400; +2, 400&lt;=gen&lt;450; +2]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg4&gt;0.659) ? ((arg7&gt;0.664) ? (EVIL) : ((arg9&gt;0.662) ? ((arg0&gt;0.66) ? (BUY) : (SELL)) : ((arg5&gt;0.664) ? ((arg13&gt;0.659) ? (SELL) : (BUY)) : ((arg1&gt;0.662) ? ((arg12&gt;0.662) ? (SELL) : (BUY)) : ((arg14&gt;0.661) ? ((arg11&gt;0.662) ? (BUY) : (EVIL)) : (BUY)))))) : (EVIL)<br />
                                Base fitness: 0.037037037037037035<br />
                                Test set base fitness: 0.4444444444444444<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    38.687s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"gbpeur", [50<=gen<100; +1, 100<=gen<150; +2, 150<=gen<200; +3, 200<=gen<250; +4, 250<=gen<300; +5, 350<=gen<400; +6, 400<=gen<450; +7], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 gbpeur RangeModifier6<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;150; +2, 150&lt;=gen&lt;200; +3, 200&lt;=gen&lt;250; +4, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +6, 400&lt;=gen&lt;450; +7]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;150; +2, 150&lt;=gen&lt;200; +3, 200&lt;=gen&lt;250; +4, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +6, 400&lt;=gen&lt;450; +7]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg6&gt;1.147) ? ((arg5&gt;1.121) ? (SELL) : (BUY)) : ((arg0&gt;1.12) ? ((arg2&gt;1.12) ? (SELL) : ((arg1&gt;1.091) ? ((arg10&gt;1.095) ? ((arg12&gt;1.088) ? ((arg13&gt;1.096) ? ((arg14&gt;1.113) ? ((arg4&gt;1.091) ? (BUY) : (SELL)) : ((arg8&gt;1.088) ? ((arg11&gt;1.125) ? ((arg4&gt;1.091) ? (BUY) : (SELL)) : (BUY)) : (BUY))) : ((arg11&gt;1.125) ? (SELL) : ((arg8&gt;1.088) ? (SELL) : (BUY)))) : ((arg11&gt;1.125) ? (SELL) : (BUY))) : ((arg12&gt;1.088) ? ((arg14&gt;1.113) ? (EVIL) : (SELL)) : ((arg4&gt;1.091) ? (SELL) : ((arg13&gt;1.096) ? (BUY) : (SELL))))) : ((arg14&gt;1.113) ? (BUY) : ((arg4&gt;1.091) ? ((arg10&gt;1.127) ? ((arg12&gt;1.088) ? (SELL) : ((arg13&gt;1.096) ? (BUY) : ((arg11&gt;1.125) ? (SELL) : (EVIL)))) : (SELL)) : ((arg12&gt;1.088) ? ((arg13&gt;1.096) ? (BUY) : ((arg10&gt;1.127) ? ((arg9&gt;1.094) ? (BUY) : (SELL)) : (BUY))) : (BUY)))))) : ((arg14&gt;1.113) ? ((arg7&gt;1.088) ? ((arg4&gt;1.091) ? ((arg10&gt;1.127) ? ((arg12&gt;1.088) ? (BUY) : (SELL)) : (SELL)) : ((arg12&gt;1.088) ? ((arg11&gt;1.125) ? (SELL) : (BUY)) : ((arg13&gt;1.096) ? (BUY) : ((arg2&gt;1.12) ? ((arg8&gt;1.088) ? (SELL) : ((arg10&gt;1.095) ? (SELL) : ((arg11&gt;1.125) ? (SELL) : (BUY)))) : (SELL))))) : (BUY)) : ((arg8&gt;1.088) ? ((arg11&gt;1.125) ? (SELL) : (BUY)) : ((arg10&gt;1.095) ? (SELL) : ((arg12&gt;1.088) ? ((arg13&gt;1.096) ? (BUY) : (SELL)) : (BUY))))))<br />
                                Base fitness: 0.06481481481481481<br />
                                Test set base fitness: 0.7777777777777778<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    33.109s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"gbpeur", [50<=gen<100; +3, 100<=gen<150; +0, 150<=gen<200; +4, 200<=gen<250; +0, 250<=gen<300; +5, 350<=gen<400; +0, 400<=gen<450; +7], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 gbpeur RangeModifier7<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +3, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +4, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +7]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +3, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +4, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +7]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg14&gt;1.114) ? ((arg5&gt;1.102) ? ((arg1&gt;1.119) ? ((arg13&gt;1.112) ? (SELL) : (BUY)) : ((arg3&gt;1.126) ? ((arg7&gt;1.106) ? ((arg4&gt;1.101) ? ((arg0&gt;1.082) ? ((arg9&gt;1.091) ? (BUY) : (SELL)) : (EVIL)) : ((arg9&gt;1.091) ? ((arg8&gt;1.121) ? (EVIL) : ((arg10&gt;1.119) ? (BUY) : (SELL))) : (BUY))) : (SELL)) : ((arg8&gt;1.121) ? (BUY) : (SELL)))) : ((arg0&gt;1.082) ? (BUY) : ((arg1&gt;1.119) ? (SELL) : ((arg8&gt;1.121) ? (BUY) : (SELL))))) : ((arg0&gt;1.12) ? ((arg1&gt;1.119) ? (SELL) : ((arg9&gt;1.091) ? (BUY) : ((arg8&gt;1.091) ? (BUY) : (SELL)))) : ((arg1&gt;1.119) ? ((arg9&gt;1.115) ? (SELL) : (BUY)) : ((arg3&gt;1.126) ? ((arg5&gt;1.102) ? (SELL) : ((arg9&gt;1.103) ? (BUY) : ((arg4&gt;1.101) ? (SELL) : (BUY)))) : ((arg9&gt;1.091) ? ((arg8&gt;1.091) ? (BUY) : (SELL)) : ((arg4&gt;1.101) ? (SELL) : (BUY))))))<br />
                                Base fitness: 0.07407407407407407<br />
                                Test set base fitness: 0.8888888888888888<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    11.422s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"cadeur", [50<=gen<100; +1, 100<=gen<200; +2, 200<=gen<500; +3, 500<=gen<1,000; +4], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 cadeur RangeModifier10<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;200; +2, 200&lt;=gen&lt;500; +3, 500&lt;=gen&lt;1,000; +4]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;200; +2, 200&lt;=gen&lt;500; +3, 500&lt;=gen&lt;1,000; +4]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg13&gt;0.653) ? ((arg8&gt;0.634) ? ((arg6&gt;0.645) ? ((arg2&gt;0.647) ? ((arg12&gt;0.637) ? (SELL) : ((arg3&gt;0.633) ? (BUY) : (SELL))) : (BUY)) : (SELL)) : (EVIL)) : ((arg9&gt;0.646) ? (SELL) : ((arg4&gt;0.652) ? (SELL) : ((arg1&gt;0.627) ? (BUY) : ((arg14&gt;0.639) ? (SELL) : (BUY)))))<br />
                                Base fitness: 0.018518518518518517<br />
                                Test set base fitness: 0.2222222222222222<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    47.157s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"chfeur", [50<=gen<100; +3, 100<=gen<150; +0, 150<=gen<200; +4, 200<=gen<250; +0, 250<=gen<300; +5, 350<=gen<400; +0, 400<=gen<450; +7], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 chfeur RangeModifier2<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +3, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +4, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +7]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +3, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +4, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +7]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg7&gt;0.659) ? ((arg0&gt;0.662) ? ((arg14&gt;0.668) ? ((arg9&gt;0.66) ? (BUY) : (SELL)) : ((arg6&gt;0.659) ? ((arg12&gt;0.662) ? ((arg1&gt;0.662) ? ((arg5&gt;0.662) ? (BUY) : ((arg11&gt;0.662) ? (SELL) : (EVIL))) : (EVIL)) : (BUY)) : (EVIL))) : ((arg14&gt;0.661) ? ((arg11&gt;0.662) ? ((arg3&gt;0.66) ? ((arg1&gt;0.661) ? ((arg9&gt;0.669) ? ((arg2&gt;0.66) ? (EVIL) : ((arg6&gt;0.659) ? (BUY) : (EVIL))) : ((arg10&gt;0.662) ? (BUY) : ((arg5&gt;0.661) ? (BUY) : (EVIL)))) : (SELL)) : ((arg1&gt;0.661) ? (BUY) : (SELL))) : ((arg6&gt;0.659) ? (EVIL) : (SELL))) : ((arg1&gt;0.661) ? ((arg10&gt;0.663) ? (SELL) : (BUY)) : ((arg2&gt;0.66) ? ((arg10&gt;0.662) ? (SELL) : ((arg11&gt;0.662) ? (BUY) : (EVIL))) : (BUY))))) : ((arg14&gt;0.668) ? ((arg1&gt;0.662) ? (EVIL) : ((arg10&gt;0.662) ? ((arg12&gt;0.662) ? (BUY) : (SELL)) : (EVIL))) : ((arg3&gt;0.66) ? ((arg11&gt;0.662) ? ((arg12&gt;0.662) ? ((arg0&gt;0.662) ? (BUY) : ((arg5&gt;0.661) ? ((arg1&gt;0.661) ? ((arg9&gt;0.669) ? ((arg6&gt;0.659) ? (EVIL) : (SELL)) : (BUY)) : (BUY)) : (EVIL))) : (BUY)) : ((arg1&gt;0.661) ? (BUY) : ((arg2&gt;0.66) ? (SELL) : (BUY)))) : ((arg6&gt;0.659) ? ((arg0&gt;0.662) ? (EVIL) : ((arg2&gt;0.66) ? (BUY) : (EVIL))) : ((arg1&gt;0.662) ? ((arg9&gt;0.669) ? (SELL) : (BUY)) : ((arg0&gt;0.662) ? (EVIL) : ((arg10&gt;0.662) ? (BUY) : ((arg2&gt;0.66) ? (EVIL) : ((arg11&gt;0.662) ? (BUY) : (EVIL)))))))))<br />
                                Base fitness: 0.046296296296296294<br />
                                Test set base fitness: 0.5555555555555556<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    26.078s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"cadeur", [300<=gen<600; +1, 600<=gen<1,000; +3], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 cadeur RangeModifier14<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [300&lt;=gen&lt;600; +1, 600&lt;=gen&lt;1,000; +3]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [300&lt;=gen&lt;600; +1, 600&lt;=gen&lt;1,000; +3]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg6&gt;0.655) ? ((arg4&gt;0.652) ? (EVIL) : (BUY)) : ((arg14&gt;0.632) ? ((arg13&gt;0.648) ? ((arg1&gt;0.64) ? ((arg8&gt;0.656) ? ((arg9&gt;0.648) ? (SELL) : (BUY)) : (BUY)) : ((arg5&gt;0.638) ? ((arg9&gt;0.648) ? (SELL) : (BUY)) : (SELL))) : ((arg3&gt;0.638) ? (SELL) : ((arg5&gt;0.638) ? ((arg1&gt;0.64) ? ((arg2&gt;0.628) ? (BUY) : (SELL)) : (SELL)) : ((arg7&gt;0.653) ? (SELL) : ((arg1&gt;0.627) ? ((arg2&gt;0.628) ? (BUY) : ((arg8&gt;0.637) ? (BUY) : (SELL))) : (SELL)))))) : ((arg9&gt;0.648) ? ((arg13&gt;0.648) ? ((arg1&gt;0.64) ? ((arg8&gt;0.656) ? (SELL) : (BUY)) : ((arg5&gt;0.638) ? (SELL) : (BUY))) : ((arg3&gt;0.638) ? ((arg4&gt;0.629) ? (BUY) : ((arg8&gt;0.637) ? (BUY) : (SELL))) : ((arg1&gt;0.64) ? (SELL) : (BUY)))) : ((arg4&gt;0.629) ? (BUY) : ((arg1&gt;0.64) ? (BUY) : (SELL)))))<br />
                                Base fitness: 0.06481481481481481<br />
                                Test set base fitness: 0.7777777777777778<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    58.281s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"chfeur", [50<=gen<100; +7, 100<=gen<150; +0, 150<=gen<200; +5, 200<=gen<250; +0, 250<=gen<300; +3, 350<=gen<400; +0, 400<=gen<450; +1], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 chfeur RangeModifier3<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +7, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +5, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +3, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +1]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +7, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +5, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +3, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +1]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg12&gt;0.663) ? ((arg13&gt;0.669) ? ((arg9&gt;0.661) ? ((arg1&gt;0.661) ? ((arg8&gt;0.664) ? (EVIL) : ((arg2&gt;0.662) ? (BUY) : ((arg0&gt;0.66) ? (BUY) : (EVIL)))) : (EVIL)) : ((arg2&gt;0.662) ? (SELL) : ((arg14&gt;0.661) ? ((arg6&gt;0.662) ? ((arg3&gt;0.663) ? ((arg7&gt;0.661) ? (BUY) : (SELL)) : ((arg1&gt;0.661) ? (SELL) : (EVIL))) : (EVIL)) : ((arg3&gt;0.663) ? (BUY) : ((arg0&gt;0.66) ? ((arg10&gt;0.662) ? ((arg1&gt;0.661) ? (EVIL) : (BUY)) : (EVIL)) : (BUY)))))) : ((arg9&gt;0.661) ? ((arg2&gt;0.662) ? (SELL) : ((arg0&gt;0.66) ? ((arg7&gt;0.661) ? (BUY) : (SELL)) : ((arg3&gt;0.663) ? (EVIL) : (SELL)))) : ((arg1&gt;0.661) ? ((arg0&gt;0.66) ? (BUY) : ((arg7&gt;0.661) ? (EVIL) : ((arg5&gt;0.662) ? (EVIL) : (SELL)))) : (SELL)))) : ((arg14&gt;0.661) ? ((arg13&gt;0.662) ? ((arg6&gt;0.662) ? ((arg9&gt;0.661) ? ((arg1&gt;0.661) ? ((arg3&gt;0.663) ? (BUY) : ((arg0&gt;0.66) ? (EVIL) : ((arg7&gt;0.661) ? (SELL) : (BUY)))) : (SELL)) : ((arg1&gt;0.661) ? ((arg5&gt;0.662) ? (BUY) : (EVIL)) : (SELL))) : ((arg9&gt;0.661) ? ((arg1&gt;0.661) ? ((arg5&gt;0.662) ? (BUY) : (EVIL)) : (SELL)) : (SELL))) : ((arg3&gt;0.663) ? ((arg7&gt;0.661) ? ((arg9&gt;0.661) ? ((arg1&gt;0.661) ? (BUY) : (SELL)) : ((arg2&gt;0.662) ? (SELL) : ((arg1&gt;0.661) ? (BUY) : (SELL)))) : ((arg6&gt;0.662) ? (SELL) : (EVIL))) : ((arg9&gt;0.661) ? ((arg1&gt;0.661) ? (EVIL) : ((arg0&gt;0.66) ? (EVIL) : (SELL))) : ((arg0&gt;0.66) ? ((arg7&gt;0.661) ? (EVIL) : ((arg1&gt;0.661) ? (SELL) : (EVIL))) : ((arg7&gt;0.66) ? (EVIL) : (SELL)))))) : ((arg5&gt;0.659) ? (BUY) : (EVIL)))<br />
                                Base fitness: 0.037037037037037035<br />
                                Test set base fitness: 0.4444444444444444<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    36.563s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"gbpeur", [50<=gen<100; +1, 100<=gen<200; +2, 200<=gen<500; +3, 500<=gen<1,000; +4], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 gbpeur RangeModifier5<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;200; +2, 200&lt;=gen&lt;500; +3, 500&lt;=gen&lt;1,000; +4]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;200; +2, 200&lt;=gen&lt;500; +3, 500&lt;=gen&lt;1,000; +4]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg10&gt;1.128) ? ((arg5&gt;1.119) ? (SELL) : (BUY)) : ((arg0&gt;1.114) ? ((arg1&gt;1.139) ? ((arg5&gt;1.103) ? (SELL) : ((arg14&gt;1.113) ? ((arg13&gt;1.107) ? ((arg4&gt;1.128) ? (BUY) : ((arg8&gt;1.112) ? (SELL) : (BUY))) : ((arg3&gt;1.111) ? (SELL) : ((arg4&gt;1.128) ? (SELL) : (BUY)))) : ((arg8&gt;1.112) ? (BUY) : ((arg12&gt;1.091) ? (BUY) : ((arg3&gt;1.111) ? ((arg7&gt;1.144) ? (BUY) : (SELL)) : (BUY)))))) : ((arg8&gt;1.112) ? (SELL) : ((arg5&gt;1.103) ? ((arg3&gt;1.111) ? ((arg7&gt;1.144) ? (SELL) : ((arg14&gt;1.113) ? (SELL) : ((arg12&gt;1.091) ? (BUY) : (SELL)))) : ((arg9&gt;1.116) ? (EVIL) : (SELL))) : ((arg13&gt;1.107) ? (SELL) : (BUY))))) : ((arg14&gt;1.113) ? ((arg3&gt;1.111) ? ((arg8&gt;1.112) ? ((arg9&gt;1.116) ? ((arg4&gt;1.128) ? ((arg5&gt;1.103) ? (SELL) : (BUY)) : (BUY)) : ((arg7&gt;1.112) ? (SELL) : ((arg12&gt;1.091) ? (BUY) : (SELL)))) : (BUY)) : ((arg1&gt;1.098) ? ((arg5&gt;1.103) ? (SELL) : ((arg8&gt;1.112) ? ((arg9&gt;1.116) ? ((arg4&gt;1.128) ? (SELL) : (BUY)) : (SELL)) : ((arg12&gt;1.091) ? (BUY) : (SELL)))) : ((arg11&gt;1.101) ? ((arg8&gt;1.112) ? (SELL) : ((arg5&gt;1.103) ? (SELL) : ((arg4&gt;1.128) ? (SELL) : (BUY)))) : (SELL)))) : (BUY)))<br />
                                Base fitness: 0.08333333333333333<br />
                                Test set base fitness: 1.0<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    37.156s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"chfeur", [300<=gen<600; +1, 600<=gen<1,000; +3], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 chfeur RangeModifier4<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [300&lt;=gen&lt;600; +1, 600&lt;=gen&lt;1,000; +3]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [300&lt;=gen&lt;600; +1, 600&lt;=gen&lt;1,000; +3]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg6&gt;0.664) ? (EVIL) : ((arg14&gt;0.661) ? ((arg11&gt;0.663) ? ((arg9&gt;0.668) ? (EVIL) : ((arg1&gt;0.661) ? ((arg12&gt;0.662) ? ((arg4&gt;0.661) ? (BUY) : (SELL)) : (SELL)) : ((arg10&gt;0.662) ? ((arg2&gt;0.662) ? (SELL) : ((arg13&gt;0.661) ? ((arg8&gt;0.659) ? (BUY) : (SELL)) : ((arg8&gt;0.659) ? (BUY) : (EVIL)))) : (SELL)))) : ((arg9&gt;0.662) ? ((arg13&gt;0.661) ? ((arg1&gt;0.661) ? (BUY) : ((arg0&gt;0.662) ? ((arg12&gt;0.662) ? ((arg8&gt;0.659) ? (BUY) : (EVIL)) : (EVIL)) : (EVIL))) : (SELL)) : ((arg12&gt;0.662) ? ((arg8&gt;0.659) ? ((arg10&gt;0.662) ? ((arg1&gt;0.661) ? ((arg4&gt;0.661) ? (BUY) : (EVIL)) : ((arg0&gt;0.662) ? (EVIL) : ((arg4&gt;0.661) ? (EVIL) : (SELL)))) : (SELL)) : (EVIL)) : (EVIL)))) : ((arg11&gt;0.663) ? ((arg9&gt;0.668) ? ((arg1&gt;0.661) ? (SELL) : (EVIL)) : ((arg1&gt;0.661) ? ((arg8&gt;0.659) ? ((arg13&gt;0.661) ? (BUY) : ((arg0&gt;0.662) ? (SELL) : (EVIL))) : (EVIL)) : ((arg2&gt;0.662) ? (BUY) : (SELL)))) : ((arg1&gt;0.659) ? (BUY) : ((arg9&gt;0.662) ? ((arg12&gt;0.662) ? ((arg4&gt;0.661) ? ((arg13&gt;0.661) ? (BUY) : (SELL)) : (EVIL)) : ((arg13&gt;0.661) ? ((arg2&gt;0.664) ? (SELL) : (EVIL)) : (EVIL))) : ((arg12&gt;0.662) ? (SELL) : (EVIL))))))<br />
                                Base fitness: 0.037037037037037035<br />
                                Test set base fitness: 0.4444444444444444<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    40.984s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"gbpeur", [300<=gen<600; +1, 600<=gen<1,000; +3], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 gbpeur RangeModifier9<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [300&lt;=gen&lt;600; +1, 600&lt;=gen&lt;1,000; +3]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [300&lt;=gen&lt;600; +1, 600&lt;=gen&lt;1,000; +3]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg11&gt;1.144) ? ((arg13&gt;1.112) ? (BUY) : (SELL)) : ((arg14&gt;1.116) ? ((arg5&gt;1.102) ? (SELL) : ((arg1&gt;1.123) ? ((arg6&gt;1.109) ? ((arg3&gt;1.103) ? ((arg13&gt;1.098) ? (SELL) : ((arg4&gt;1.109) ? (SELL) : (BUY))) : (SELL)) : ((arg0&gt;1.115) ? (SELL) : ((arg3&gt;1.103) ? (BUY) : (EVIL)))) : ((arg0&gt;1.115) ? ((arg6&gt;1.109) ? ((arg4&gt;1.109) ? ((arg7&gt;1.115) ? ((arg10&gt;1.109) ? (BUY) : ((arg12&gt;1.11) ? (BUY) : (SELL))) : ((arg9&gt;1.107) ? (BUY) : (SELL))) : (SELL)) : ((arg13&gt;1.098) ? ((arg10&gt;1.109) ? (SELL) : ((arg7&gt;1.072) ? (BUY) : ((arg9&gt;1.107) ? (BUY) : (SELL)))) : ((arg4&gt;1.109) ? (BUY) : (SELL)))) : ((arg3&gt;1.103) ? ((arg13&gt;1.098) ? (BUY) : (SELL)) : ((arg4&gt;1.109) ? (SELL) : ((arg7&gt;1.072) ? (BUY) : (SELL))))))) : ((arg0&gt;1.115) ? ((arg6&gt;1.109) ? ((arg4&gt;1.109) ? ((arg7&gt;1.115) ? (SELL) : ((arg9&gt;1.107) ? (BUY) : (SELL))) : (SELL)) : ((arg13&gt;1.098) ? ((arg10&gt;1.109) ? (SELL) : (BUY)) : ((arg1&gt;1.123) ? (SELL) : ((arg4&gt;1.109) ? (BUY) : (SELL))))) : ((arg3&gt;1.103) ? ((arg13&gt;1.098) ? (BUY) : (SELL)) : ((arg4&gt;1.109) ? (SELL) : ((arg7&gt;1.072) ? ((arg9&gt;1.107) ? ((arg6&gt;1.109) ? (SELL) : (BUY)) : ((arg6&gt;1.109) ? (SELL) : (BUY))) : (SELL))))))<br />
                                Base fitness: 0.05555555555555555<br />
                                Test set base fitness: 0.6666666666666666<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    6.468s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"chfeur", [50<=gen<100; +0, 100<=gen<200; +1, 200<=gen<500; +1, 500<=gen<1,000; +2], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 chfeur RangeModifier0<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +0, 100&lt;=gen&lt;200; +1, 200&lt;=gen&lt;500; +1, 500&lt;=gen&lt;1,000; +2]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +0, 100&lt;=gen&lt;200; +1, 200&lt;=gen&lt;500; +1, 500&lt;=gen&lt;1,000; +2]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg4&gt;0.659) ? ((arg13&gt;0.67) ? (EVIL) : ((arg3&gt;0.662) ? ((arg2&gt;0.662) ? ((arg14&gt;0.662) ? (SELL) : (BUY)) : (EVIL)) : ((arg11&gt;0.663) ? ((arg14&gt;0.662) ? ((arg0&gt;0.662) ? (SELL) : (BUY)) : (SELL)) : ((arg14&gt;0.661) ? ((arg1&gt;0.663) ? (BUY) : ((arg6&gt;0.659) ? (EVIL) : ((arg9&gt;0.659) ? ((arg2&gt;0.663) ? (BUY) : (SELL)) : (SELL)))) : (BUY))))) : (EVIL)<br />
                                Base fitness: 0.037037037037037035<br />
                                Test set base fitness: 0.4444444444444444<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    56.407s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"gbpeur", [50<=gen<100; +7, 100<=gen<150; +0, 150<=gen<200; +5, 200<=gen<250; +0, 250<=gen<300; +3, 350<=gen<400; +0, 400<=gen<450; +1], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 gbpeur RangeModifier8<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +7, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +5, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +3, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +1]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +7, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +5, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +3, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +1]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg14&gt;1.118) ? ((arg6&gt;1.076) ? (SELL) : ((arg2&gt;1.121) ? ((arg0&gt;1.12) ? ((arg4&gt;1.112) ? ((arg9&gt;1.095) ? (EVIL) : (SELL)) : (SELL)) : ((arg3&gt;1.095) ? ((arg11&gt;1.115) ? (BUY) : (SELL)) : ((arg1&gt;1.114) ? (EVIL) : ((arg5&gt;1.104) ? (SELL) : (EVIL))))) : ((arg3&gt;1.095) ? ((arg4&gt;1.112) ? ((arg10&gt;1.095) ? (BUY) : (SELL)) : ((arg10&gt;1.095) ? ((arg11&gt;1.104) ? (SELL) : (BUY)) : ((arg11&gt;1.104) ? (SELL) : (BUY)))) : (BUY)))) : ((arg2&gt;1.121) ? ((arg0&gt;1.12) ? (SELL) : ((arg1&gt;1.114) ? ((arg3&gt;1.095) ? (BUY) : ((arg5&gt;1.104) ? (SELL) : (EVIL))) : ((arg5&gt;1.104) ? (SELL) : ((arg11&gt;1.087) ? ((arg10&gt;1.095) ? ((arg9&gt;1.095) ? (BUY) : (SELL)) : (BUY)) : (BUY))))) : ((arg3&gt;1.095) ? ((arg10&gt;1.095) ? ((arg1&gt;1.114) ? ((arg4&gt;1.112) ? ((arg9&gt;1.119) ? (SELL) : (BUY)) : ((arg11&gt;1.104) ? (SELL) : ((arg12&gt;1.076) ? (BUY) : (SELL)))) : ((arg9&gt;1.095) ? (BUY) : (SELL))) : ((arg0&gt;1.119) ? (SELL) : ((arg11&gt;1.087) ? ((arg6&gt;1.076) ? (SELL) : (BUY)) : (BUY)))) : ((arg1&gt;1.114) ? ((arg4&gt;1.112) ? (SELL) : ((arg11&gt;1.104) ? (SELL) : (BUY))) : ((arg5&gt;1.104) ? (SELL) : ((arg10&gt;1.095) ? ((arg9&gt;1.095) ? (BUY) : (SELL)) : (BUY))))))<br />
                                Base fitness: 0.05555555555555555<br />
                                Test set base fitness: 0.6666666666666666<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    22.718s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"cadeur", [50<=gen<100; +3, 100<=gen<150; +0, 150<=gen<200; +4, 200<=gen<250; +0, 250<=gen<300; +5, 350<=gen<400; +0, 400<=gen<450; +7], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 cadeur RangeModifier12<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +3, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +4, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +7]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +3, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +4, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +7]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg4&gt;0.637) ? ((arg8&gt;0.647) ? ((arg10&gt;0.654) ? ((arg7&gt;0.655) ? (SELL) : (BUY)) : (SELL)) : ((arg12&gt;0.636) ? ((arg11&gt;0.638) ? ((arg5&gt;0.633) ? (BUY) : (SELL)) : (SELL)) : ((arg14&gt;0.636) ? ((arg10&gt;0.654) ? ((arg11&gt;0.638) ? ((arg0&gt;0.628) ? (BUY) : (SELL)) : (BUY)) : (SELL)) : ((arg1&gt;0.625) ? (BUY) : (SELL))))) : ((arg1&gt;0.625) ? ((arg12&gt;0.648) ? (SELL) : ((arg0&gt;0.628) ? (BUY) : ((arg14&gt;0.636) ? (SELL) : (BUY)))) : (SELL))<br />
                                Base fitness: 0.018518518518518517<br />
                                Test set base fitness: 0.2222222222222222<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    28.641s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"cadeur", [50<=gen<100; +1, 100<=gen<150; +2, 150<=gen<200; +3, 200<=gen<250; +4, 250<=gen<300; +5, 350<=gen<400; +6, 400<=gen<450; +7], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 cadeur RangeModifier11<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;150; +2, 150&lt;=gen&lt;200; +3, 200&lt;=gen&lt;250; +4, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +6, 400&lt;=gen&lt;450; +7]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +1, 100&lt;=gen&lt;150; +2, 150&lt;=gen&lt;200; +3, 200&lt;=gen&lt;250; +4, 250&lt;=gen&lt;300; +5, 350&lt;=gen&lt;400; +6, 400&lt;=gen&lt;450; +7]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg13&gt;0.654) ? ((arg4&gt;0.65) ? (SELL) : (BUY)) : ((arg5&gt;0.656) ? (BUY) : ((arg12&gt;0.638) ? ((arg10&gt;0.632) ? ((arg2&gt;0.653) ? (SELL) : ((arg8&gt;0.646) ? ((arg9&gt;0.64) ? (SELL) : ((arg7&gt;0.636) ? ((arg14&gt;0.633) ? (SELL) : (BUY)) : ((arg3&gt;0.64) ? (SELL) : (BUY)))) : ((arg9&gt;0.64) ? ((arg14&gt;0.633) ? ((arg7&gt;0.636) ? (BUY) : (SELL)) : (SELL)) : (SELL)))) : ((arg14&gt;0.633) ? ((arg7&gt;0.636) ? (BUY) : ((arg3&gt;0.64) ? (SELL) : ((arg6&gt;0.637) ? (SELL) : (BUY)))) : ((arg8&gt;0.646) ? (BUY) : (SELL)))) : ((arg8&gt;0.646) ? ((arg6&gt;0.637) ? (SELL) : ((arg9&gt;0.64) ? (BUY) : (SELL))) : ((arg2&gt;0.653) ? ((arg9&gt;0.64) ? (BUY) : (SELL)) : ((arg14&gt;0.633) ? ((arg7&gt;0.636) ? (SELL) : ((arg3&gt;0.64) ? (SELL) : (BUY))) : (BUY))))))<br />
                                Base fitness: 0.018518518518518517<br />
                                Test set base fitness: 0.2222222222222222<br />
                  </div>
    

      </td>
</tr>
<tr>
  <td class="method">
          testRangeModifier
      </td>
  <td class="duration">
    48.391s
  </td>
  <td class="result">
        
          <i>Method Arguments: </i><span class="arguments">"cadeur", [50<=gen<100; +7, 100<=gen<150; +0, 150<=gen<200; +5, 200<=gen<250; +0, 250<=gen<300; +3, 350<=gen<400; +0, 400<=gen<450; +1], 0.6, 1000, 2, 1000, 20</span><br />
    
            <div class="testOutput">
                        TestConfig { <br/>
 cadeur RangeModifier13<br/>
 sub tree max depth: 2<br/>
 population size: 1000<br/>
 elite count: 20<br/>
 fitness: The number of incorrectly classified instances. [NoOpModifier]<br/>
 operators: [Mutation(probability: 0.6 bias modifier: [50&lt;=gen&lt;100; +7, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +5, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +3, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +1]}, Crossover(sub tree switching), Simplification(replaces decision nodes where both children targets are the same with a single leaf)]<br/>
 observers: [NoOpModifier, [50&lt;=gen&lt;100; +7, 100&lt;=gen&lt;150; +0, 150&lt;=gen&lt;200; +5, 200&lt;=gen&lt;250; +0, 250&lt;=gen&lt;300; +3, 350&lt;=gen&lt;400; +0, 400&lt;=gen&lt;450; +1]]<br/>
 random number generator: MersenneTwisterRNG<br/>
 selection strategy: Roulette Wheel Selection<br/>
};<br />
                                (arg2&gt;0.654) ? ((arg9&gt;0.636) ? ((arg12&gt;0.663) ? ((arg11&gt;0.633) ? (SELL) : (EVIL)) : (SELL)) : (EVIL)) : ((arg0&gt;0.643) ? ((arg4&gt;0.65) ? ((arg7&gt;0.646) ? ((arg10&gt;0.646) ? ((arg14&gt;0.652) ? ((arg12&gt;0.663) ? (EVIL) : ((arg8&gt;0.638) ? (SELL) : ((arg9&gt;0.627) ? (SELL) : (BUY)))) : (SELL)) : ((arg1&gt;0.625) ? ((arg14&gt;0.652) ? ((arg3&gt;0.639) ? (SELL) : (BUY)) : (SELL)) : ((arg14&gt;0.652) ? (SELL) : (BUY)))) : ((arg8&gt;0.638) ? ((arg3&gt;0.639) ? ((arg1&gt;0.625) ? ((arg14&gt;0.652) ? (BUY) : (SELL)) : (SELL)) : ((arg13&gt;0.637) ? (SELL) : ((arg14&gt;0.652) ? ((arg5&gt;0.652) ? (SELL) : ((arg12&gt;0.663) ? (BUY) : ((arg10&gt;0.646) ? (EVIL) : (SELL)))) : (SELL)))) : ((arg9&gt;0.636) ? (SELL) : ((arg1&gt;0.625) ? (BUY) : ((arg12&gt;0.63) ? (BUY) : (SELL)))))) : ((arg7&gt;0.631) ? (BUY) : (SELL))) : ((arg7&gt;0.646) ? ((arg10&gt;0.646) ? ((arg14&gt;0.652) ? ((arg4&gt;0.65) ? ((arg12&gt;0.63) ? (BUY) : (SELL)) : (SELL)) : ((arg4&gt;0.638) ? (SELL) : (EVIL))) : ((arg1&gt;0.625) ? ((arg14&gt;0.652) ? (BUY) : (SELL)) : (EVIL))) : ((arg10&gt;0.646) ? ((arg4&gt;0.638) ? (BUY) : (SELL)) : ((arg3&gt;0.639) ? (SELL) : ((arg1&gt;0.625) ? (BUY) : (SELL))))))<br />
                                Base fitness: 0.018518518518518517<br />
                                Test set base fitness: 0.2222222222222222<br />
                  </div>
    

      </td>
</tr>
      </table>
  
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